{"schemaVersion":"jobsearcher.job.v1","id":"ab6cf50c1361ac7ea61b08c3","url":"https://jobsearcher.com/jobs/ab6cf50c1361ac7ea61b08c3","canonicalUrl":"https://jobsearcher.com/jobs/ab6cf50c1361ac7ea61b08c3","title":"Level 2 – Technical Support Engineer","description":"About the Role\n\nLakeFusion is seeking a Technical Support Engineer (Level 2) to handle complex, escalated issues across our Master Data Management platform, built natively on the Databricks Data Intelligence Platform. In this role, you will take ownership of advanced troubleshooting and root cause analysis across the full platform stack, ensuring reliability and performance for enterprise customers.\n\nYou will work hands-on to diagnose and resolve issues related to data pipelines, entity matching, survivorship, and platform integrations. This includes analyzing logs, querying data directly, reproducing issues in isolated environments, and interpreting pipeline behavior to identify and resolve failures.\n\nWorking closely with engineering, QA, and product teams, you will escalate confirmed bugs with clear context, validate fixes, and contribute to improving system stability. You will also proactively monitor system health, support complex customer configurations, and enhance internal documentation and troubleshooting processes.\n\nThis is a highly analytical and self-directed role suited for someone who thrives in a fast-paced environment, where solving complex technical challenges and ensuring a seamless customer experience are central to success.\n\nWhat you'll do\nOwn escalated tickets from Level 1, performing in-depth root cause analysis across the LakeFusion platform stack — from ingestion and blocking through entity matching, survivorship, and golden record output\nDiagnose and resolve complex issues involving Databricks Workflows and notebooks, Delta table schema mismatches, Vector Search configuration and query failures, Spark job failures, and REST API integration errors\nReproduce customer issues in isolated environments; gather and analyze Spark logs, Databricks cluster event logs, and Delta transaction logs to isolate failure points\nQuery and analyze Databricks SQL or Unity Catalog tables directly to investigate data quality issues, deduplication anomalies, survivorship rule misfires, and match score discrepancies\nRead and interpret LakeFusion Python pipeline code to understand execution context when triaging bugs or unexpected behavior\nCollaborate with engineering and product teams to escalate confirmed bugs with clear reproduction steps, log evidence, and environment details; validate fixes in staging before customer delivery\nMonitor system health, job run history, and data flow metrics to proactively surface and address issues before customers report them\nAssist enterprise customers with complex configuration scenarios including multi-source matching, custom survivorship rules, cross-walk management, and Lakebase integration\nMaintain and improve internal and external knowledge base documentation — known issues, troubleshooting runbooks, and best practices\nWhat we're looking for\n3+ years of experience in technical support, application support, or a data-focused engineering role in a SaaS or cloud data environment\nWorking proficiency in SQL — comfortable writing investigative queries against Delta tables, reading query plans, and interpreting results in a Databricks SQL or Unity Catalog context\nHands-on experience with Databricks — running notebooks, reading Spark UI output, interpreting cluster logs, and understanding job/workflow configuration\nSolid understanding of data management concepts: entity resolution, deduplication, master data, data quality, and pipeline architecture\nAbility to read Python code confidently — not necessarily write production code from scratch, but enough to follow pipeline logic, understand function signatures, and interpret error tracebacks\nStrong analytical and problem-solving skills with high attention to detail\nExperience with ticketing and incident management tools (e.g., Zendesk, Jira, ServiceNow)\nAbility to communicate complex technical issues clearly to both technical and non-technical audiences\nComfort working cross-functionally with engineering, QA, and product teams\nNice-to-have\nExperience with Databricks Vector Search, Databricks Model Serving, or Unity Catalog\nFamiliarity with Delta Lake internals — transaction logs, CDF (Change Data Feed), schema evolution, MERGE behavior\nExposure to MDM platforms, entity matching concepts, or data stewardship workflows\nExperience with Snowflake or Microsoft Fabric as alternative lakehouse platforms\nPython scripting ability beyond reading — e.g., writing diagnostic scripts, notebook cells, or small utilities\nFamiliarity with Azure infrastructure (AKS, Azure Entra ID, Azure networking) given LakeFusion's deployment model\nExperience supporting enterprise-level customers or high-availability data systems\nBackground in healthcare data, financial services data, or other regulated data domains\nIT certifications (e.g., ITIL Foundation, Databricks Certified Associate)\nAbout LakeFusion\n\nLakeFusion is the modern Master Data Management (MDM) company. Global enterprises across industries ranging from retail to manufacturing and financial services rely on the LakeFusion platform to unify, govern, and deliver trusted data entities such as customers, products, suppliers, and employees. Built natively on the Databricks Lakehouse, LakeFusion creates a single source of truth that powers analytics and AI. LakeFusion enables organizations worldwide to accelerate innovation with trusted and governed data.","company":"Lakefusion","rawCompany":"lakefusion","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-05T16:12:40.608Z","occupations":[{"code":"15-1243.01","title":"Data Warehousing Specialists","slug":"data-warehousing-specialists"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Level 2 – Technical Support Engineer","description":"About the Role\n\nLakeFusion is seeking a Technical Support Engineer (Level 2) to handle complex, escalated issues across our Master Data Management platform, built natively on the Databricks Data Intelligence Platform. In this role, you will take ownership of advanced troubleshooting and root cause analysis across the full platform stack, ensuring reliability and performance for enterprise customers.\n\nYou will work hands-on to diagnose and resolve issues related to data pipelines, entity matching, survivorship, and platform integrations. This includes analyzing logs, querying data directly, reproducing issues in isolated environments, and interpreting pipeline behavior to identify and resolve failures.\n\nWorking closely with engineering, QA, and product teams, you will escalate confirmed bugs with clear context, validate fixes, and contribute to improving system stability. You will also proactively monitor system health, support complex customer configurations, and enhance internal documentation and troubleshooting processes.\n\nThis is a highly analytical and self-directed role suited for someone who thrives in a fast-paced environment, where solving complex technical challenges and ensuring a seamless customer experience are central to success.\n\nWhat you'll do\nOwn escalated tickets from Level 1, performing in-depth root cause analysis across the LakeFusion platform stack — from ingestion and blocking through entity matching, survivorship, and golden record output\nDiagnose and resolve complex issues involving Databricks Workflows and notebooks, Delta table schema mismatches, Vector Search configuration and query failures, Spark job failures, and REST API integration errors\nReproduce customer issues in isolated environments; gather and analyze Spark logs, Databricks cluster event logs, and Delta transaction logs to isolate failure points\nQuery and analyze Databricks SQL or Unity Catalog tables directly to investigate data quality issues, deduplication anomalies, survivorship rule misfires, and match score discrepancies\nRead and interpret LakeFusion Python pipeline code to understand execution context when triaging bugs or unexpected behavior\nCollaborate with engineering and product teams to escalate confirmed bugs with clear reproduction steps, log evidence, and environment details; validate fixes in staging before customer delivery\nMonitor system health, job run history, and data flow metrics to proactively surface and address issues before customers report them\nAssist enterprise customers with complex configuration scenarios including multi-source matching, custom survivorship rules, cross-walk management, and Lakebase integration\nMaintain and improve internal and external knowledge base documentation — known issues, troubleshooting runbooks, and best practices\nWhat we're looking for\n3+ years of experience in technical support, application support, or a data-focused engineering role in a SaaS or cloud data environment\nWorking proficiency in SQL — comfortable writing investigative queries against Delta tables, reading query plans, and interpreting results in a Databricks SQL or Unity Catalog context\nHands-on experience with Databricks — running notebooks, reading Spark UI output, interpreting cluster logs, and understanding job/workflow configuration\nSolid understanding of data management concepts: entity resolution, deduplication, master data, data quality, and pipeline architecture\nAbility to read Python code confidently — not necessarily write production code from scratch, but enough to follow pipeline logic, understand function signatures, and interpret error tracebacks\nStrong analytical and problem-solving skills with high attention to detail\nExperience with ticketing and incident management tools (e.g., Zendesk, Jira, ServiceNow)\nAbility to communicate complex technical issues clearly to both technical and non-technical audiences\nComfort working cross-functionally with engineering, QA, and product teams\nNice-to-have\nExperience with Databricks Vector Search, Databricks Model Serving, or Unity Catalog\nFamiliarity with Delta Lake internals — transaction logs, CDF (Change Data Feed), schema evolution, MERGE behavior\nExposure to MDM platforms, entity matching concepts, or data stewardship workflows\nExperience with Snowflake or Microsoft Fabric as alternative lakehouse platforms\nPython scripting ability beyond reading — e.g., writing diagnostic scripts, notebook cells, or small utilities\nFamiliarity with Azure infrastructure (AKS, Azure Entra ID, Azure networking) given LakeFusion's deployment model\nExperience supporting enterprise-level customers or high-availability data systems\nBackground in healthcare data, financial services data, or other regulated data domains\nIT certifications (e.g., ITIL Foundation, Databricks Certified Associate)\nAbout LakeFusion\n\nLakeFusion is the modern Master Data Management (MDM) company. Global enterprises across industries ranging from retail to manufacturing and financial services rely on the LakeFusion platform to unify, govern, and deliver trusted data entities such as customers, products, suppliers, and employees. Built natively on the Databricks Lakehouse, LakeFusion creates a single source of truth that powers analytics and AI. LakeFusion enables organizations worldwide to accelerate innovation with trusted and governed data.","datePosted":"2026-08-05T16:12:40.608Z","dateModified":"2026-08-05T16:12:40.608Z","hiringOrganization":{"@type":"Organization","name":"Lakefusion","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"ab6cf50c1361ac7ea61b08c3"},"url":"https://jobsearcher.com/jobs/ab6cf50c1361ac7ea61b08c3"}}